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A Denoising algorithm of MEMS Gyro Based on CEEMDAN and Improved LWT by Zhenxing Wu; Liang Shan; Daqing Rui; Jia Chen is a scholarly article available to read on EtoBox.

What is A Denoising algorithm of MEMS Gyro Based on CEEMDAN and Improved LWT about?

In view of the serious modal aliasing phenomenon in the traditional EMD method in the modal decomposition process, and the complete ensemble empirical modal decomposition method has the problem of the loss of high-frequency useful signals, this paper proposes a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) combined with improved lifting wavelet threshold(LWT) denoising algorithm for gyro signals. In order to filter the noise in the signal more effectively, the article first improves on the soft and hard threshold function denoising methods, and adopts a new wavelet threshold function. Finally, through the Matlab simulations verify the effectiveness of the algorithm. The simulation results show that CEEMDAN combined with improved lifting wavelet threshold is feasible and effective in denoising processing of MEMS gyroscope signals.

Author

Zhenxing Wu; Liang Shan; Daqing Rui; Jia Chen

Publisher

IEEE

Published

2021

Language

EN